Predicting energy cost of public buildings by artificial neural networks, CART, and random forest

Statistical change detection of building energy consumption: Applications to savings estimation

(2019) Samir Touzani et al.   ENERGY AND BUILDINGS

A comprehensive review on the application of artificial neural networks in building energy analysis

(2019) Saeed Reza Mohandes et al.   NEUROCOMPUTING

Review of building energy performance certification schemes towards future improvement

(2019) Y. Li et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Accuracy of different machine learning algorithms and added-value of predicting aggregated-level energy performance of commercial buildings

(2019) Shalika Walker et al.   ENERGY AND BUILDINGS

Reliability analysis of an energy-based form optimization of office buildings under uncertainties in envelope and occupant parameters

(2019) Shuai Lu et al.   ENERGY AND BUILDINGS

Big Data Analytics for Discovering Electricity Consumption Patterns in Smart Cities

(2018) Rubén Pérez-Chacón et al.   Energies

Neural network based optimization approach for energy demand prediction in smart grid

(2018) K. Muralitharan et al.   NEUROCOMPUTING

An Advanced IoT-based System for Intelligent Energy Management in Buildings

(2018) Vangelis Marinakis et al.   SENSORS

A scalable approach based on deep learning for big data time series forecasting

(2018) J.F. Torres et al.   INTEGRATED COMPUTER-AIDED ENGINEERING

Multi-step forecasting for big data time series based on ensemble learning

(2018) A. Galicia et al.   KNOWLEDGE-BASED SYSTEMS

Regression tree ensembles for wind energy and solar radiation prediction

(2017) Alberto Torres-Barrán et al.   NEUROCOMPUTING

Improving the accuracy of energy baseline models for commercial buildings with occupancy data

(2016) Xin Liang et al.   APPLIED ENERGY

Energy consumption prediction of office buildings based on echo state networks

(2016) Guang Shi et al.   NEUROCOMPUTING

Energy management and planning in smart cities

(2016) C.F. Calvillo et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Handling data uncertainties when using Swedish energy performance certificate data to describe energy usage in the building stock

(2015) Mikael Mangold et al.   ENERGY AND BUILDINGS

An occupant-based energy consumption prediction model for office equipment

(2015) Zhaoxia Wang et al.   ENERGY AND BUILDINGS

A better measure of relative prediction accuracy for model selection and model estimation

(2015) Chris Tofallis   JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY

Deep learning

(2015) Yann LeCun et al.   NATURE

Soft computing methodologies for estimation of energy consumption in buildings with different envelope parameters

(2015) Sareh Naji et al.   Energy Efficiency

Feature Selection with theBorutaPackage

(2015) Miron B. Kursa et al.   Journal of Statistical Software

Variable Importance Assessment in Regression: Linear Regression versus Random Forest

(2009) Ulrike Grömping   AMERICAN STATISTICIAN